A new working paper from a quartet of economists proposes a new method of estimating how we value the “non-marketed amenities” of neighborhood choices such as avoiding pollution and living among people of our own race. The old static method, they say, underestimates our willingness to pay to avoid air pollution and crime, but overstates how much we value living near neighbors of our own race. Here’s the abstract:
We develop a tractable model of neighborhood choice in a dynamic setting along with a computationally straightforward estimation approach. This approach uses information about neighborhood choices and the timing of moves to recover moving costs and preferences for dynamically-evolving housing and neighborhood attributes. The model and estimator are potentially applicable to the study of a wide range of dynamic phenomena in housing markets and cities. We focus here on estimating the marginal willingness to pay for non-marketed amenities – neighborhood racial composition, air pollution, and violent crime – using rich dynamic data. Consistent with the time-series properties of each amenity, we find that a static demand model understates willingness to pay to avoid pollution and crime but overstates willingness to pay to live near neighbors of one’s own race. These findings have important implications for the class of static housing demand models typically used to value urban amenities.
And here’s the upshot:
The findings from this exercise indicate that the preference estimates derived from our dynamic approach differ substantially from estimates derived from a comparable static demand model. For example, the per-year willingness to pay to avoid a 10-percent increase in the number violent crimes per 100,000 population is $586 (in 2000 dollars), which is about seventy percent higher than the $344 recovered from a comparable static estimation procedure. In the case of air pollution, the corresponding differences are even larger ($296 from the dynamic model versus $73 from the static) though still in the same direction. In contrast, the per-year marginal willingness to pay for race (in particular, the preferences of whites for living in proximity to other whites) is $1,558 whereas the estimate from a naive static model is substantially higher at $1,973. Given the time-series properties of each of these variables, the sign of the bias from ignoring dynamic considerations accords, in each case, with the intuition that the valuations of mean-reverting amenities will be understated while those of positively-persistent amenities will be overstated by a static model.
There’s one big caveat: the data come from San Francisco, which is itself an outlier when it comes to housing markets. It’s probably a safe bet that people in San Francisco don’t necessarily value the avoidance of pollution or living among their own race the same way the rest of the country does. Still, it’s an interesting exercise in understanding our willingness to pay for certain intangibles when shopping for a neighborhood.